Simulation and forecasting of significant wave heights and average zero-cross wave periods in real time are done for a specified location, given the past observed sequence of wind speed and wind direction. This is based on time series forecasting implemented using the two recent data-driven methods of genetic programming (GP) and model trees (MT). The wave buoy measurements made at eight different offshore locations around the west as well as the east coast in India are considered. Both genetic programming and model trees perform satisfactorily in the given task of wind-wave simulation and forecasting as reflected in the values of the six different error statistics employed to assess the performance of developed models over testing sets of data. Although the magnitudes of error statistics do not indicate a significant difference between the performance of GP and MT, qualitative scatter diagrams and time histories showed the tendency of MT to estimate higher waves more correctly.
Wave simulation and forecasting using wind time history and data-driven methods
Ships and Offshore Structures ; 5 , 3 ; 253-266
2010-09-02
Article (Journal)
Electronic Resource
Unknown
Wave simulation and forecasting using wind time history and data-driven methods
| Online Contents | 2010
Multistep-ahead flood forecasting using wavelet and data-driven methods
| Springer Verlag | 2015
Multistep-ahead flood forecasting using wavelet and data-driven methods
| Online Contents | 2015
Real time wave forecasting using neural networks
| Tema Archive | 1999